Data Scientist

Intepros Incorporated
United States
9 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Working hours
Regular working hours
Job source

Tech stack

A/B Testing Business Analytics Applications Artificial Neural Networks Big Data Health Informatics Cluster Analysis Computer Programming Data Mining Relational Databases Statistical Hypothesis Testing Logistic Regression Machine Learning
+8 more
Pattern Recognition SQL Databases Computational Statistics Unstructured Data Sql Optimization Electronic Medical Records Information Technology Data Analytics

Job description

IntePros is seeking an experienced Senior Data Scientist to join a large, complex organization and lead advanced analytics initiatives that support data-driven business and operational decision-making. This role will work with large, complex, and often unstructured data sets to identify trends, develop predictive models, test hypotheses, and translate analytical findings into meaningful business insights. The Senior Data Scientist will partner closely with business leaders, technical teams, and other stakeholders to understand complex problems and communicate findings to audiences ranging from technical teams through senior executive leadership., * Lead high-priority data science and advanced analytics initiatives with organization-wide impact.

  • Analyze large, complex, structured, and unstructured data sets to identify trends, patterns, relationships, and actionable insights.
  • Develop custom data models, algorithms, and analytical approaches to address complex business questions.
  • Build and apply predictive models and advanced statistical techniques to key business and operational metrics.
  • Perform research, statistical analysis, modeling, data mining, visualization, and pattern analysis.
  • Develop and test hypotheses and communicate findings in a clear, concise, and actionable manner.
  • Translate complex analytical findings into meaningful business insights for stakeholders and senior leadership.
  • Develop, maintain, and evaluate statistical and machine learning models, including assessment of model performance and goodness of fit.
  • Partner with cross-functional teams to identify and resolve data quality, availability, and scalability challenges.
  • Gather business requirements and determine the appropriate analytical approach for solving complex problems.
  • Present findings and recommendations to stakeholders ranging from technical teams to senior and executive leadership.
  • Provide technical leadership and mentorship to other data scientists and contribute to the development of data science capabilities across the organization.
  • Manage multiple projects and priorities while maintaining high standards for quality, accuracy, and delivery.
  • Assist in evaluating data science technologies, vendors, platforms, and analytical tools.
  • Identify opportunities to improve the efficiency, productivity, and scalability of data and analytics processes.

Requirements

The ideal candidate brings a strong combination of data science, advanced statistics, machine learning, SQL, business analytics, and executive-level communication skills. Experience working with healthcare, hospital, EHR, medical informatics, revenue cycle, or other healthcare-related data is highly preferred., * Bachelor’s degree in Computer Science, Data Science, Mathematics, Statistics, Engineering, Science, or another related STEM discipline.

  • 7+ years of professional data science experience.
  • Strong experience analyzing large, complex, and incomplete data sets.
  • Advanced knowledge of statistical methods and techniques, including:
  • Linear and logistic regression
  • Time series forecasting
  • A/B testing
  • Statistical hypothesis testing
  • Clustering
  • Distribution analysis
  • Strong understanding of machine learning techniques such as clustering, decision trees, neural networks, and predictive modeling, including the advantages and limitations of different approaches.
  • Advanced SQL skills and experience working with relational databases and large data sets.
  • Strong programming skills using languages and tools commonly associated with data science and statistical analysis.
  • Demonstrated experience developing data models, algorithms, and analytical solutions.
  • Strong understanding of the full data science project lifecycle.
  • Ability to take complex data and translate it into meaningful business information and actionable recommendations.
  • Strong analytical reasoning, troubleshooting, and problem-solving skills.
  • Experience gathering requirements and partnering directly with business stakeholders.
  • Excellent written and verbal communication skills.
  • Comfortable presenting complex analytical findings to senior and executive-level leadership.
  • Ability to communicate effectively with both technical and non-technical audiences.
  • Strong project management skills with the ability to independently manage multiple priorities and deadlines.
  • Ability to operate effectively with minimal supervision in a fast-paced, multidisciplinary environment., * Master’s degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.
  • Previous data science experience within a hospital, healthcare, or clinical environment.
  • Experience working with:
  • Electronic Health Record (EHR) data
  • Medical informatics
  • Healthcare information technology
  • Healthcare finance or revenue cycle data
  • Clinical or operational healthcare data
  • Experience mentoring or providing technical leadership to other data scientists.

What Will Make Someone Successful in This Role This position requires more than someone who can build models or write SQL. The successful candidate will be able to look at complex data, determine what it means to the business, and tell the story behind the data to senior decision-makers. Candidates should bring a highly analytical mindset while also being comfortable operating in a consultative, stakeholder-facing capacity. Strong presentation skills and the ability to simplify complex technical concepts for executive audiences will be critical.

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